OKHS Field Studies (NL)
Statistical Analysis
Building Assessment
The Oklahoma Healthy School research identified that the presence of daylight in a room has a negative association with school performance.
©Salary.S. (2017) OKHS Research Project. The University of Oklahoma. s.salary@ou.edu
Teacher's Survey Results
In 185 completed teacher surveys, the importance of "providing windows in all instructional areas" was ranked fairly low at 52 out of 92, indicating this is less important to teachers than other school factors.
©Salary.S. (2017) OKHS Research Project. The University of Oklahoma. s.salary@ou.edu
Also, the importance of "providing natural light in the storm shelter" was ranked fairly low at 81 out of 92, indicating this is less important to teachers than other school factors.
The access link to the complete list of teacher's survey and their ranking is; Teacher's Opinion
Parents' Survey Results
In a survey of 6% of parents whose children attend school in one of the two districts, the importance of "providing natural light in classrooms" was ranked fairly low at 46 out of 66, indicating this is less important to parents than other school factors.
©Salary.S. (2017) OKHS Research Project. The University of Oklahoma. s.salary@ou.edu
The access link to the complete list of teacher's survey and their ranking is; Parent's Opinion
Analysis Method for Building Assessment
We evaluated the association between architectural features in classrooms and schools and school performance. We obtained data on the features of lighting, acoustics, thermal comfort, interior design, aesthetics, and school campus by conducting physical assessments of several typical classrooms per school in two metropolitan school districts. School performance data were obtained from the State’s 2015 school report card. We used the Performance Index, which scored all schools on overall school performance with a score of 0-100 and has been standardized across all schools in the state. We used multivariable linear regression to compare the relationship between one randomly selected classroom per school and overall school performance adjusted for school-level poverty. We also accounted for clustering of schools within the two districts in our analysis. This statistical method requires the data to be independent, so we randomly selected one classroom per school to include in the analysis. By including all measured classrooms in our analysis, we would have used the statistical method inappropriately. Through our analysis, we observed that classrooms differed in relation to school performance, so we ran our analysis a second time selecting a different random classroom and compared results with our original analysis. Only the results which were consistent with both analyses were included in the tool. We excluded rooms that functioned only as gyms, safe rooms, or other non-educational rooms from the analysis. We used SAS v. 9.4 for all analyses and an alpha of 0.05 to determine statistical significance. A strength of this analysis was having detailed physical assessments of classrooms in each school and in both districts. However, a major limitation was that we did not have performance data on individual students or classrooms, but only in schools. Thus, we were unable to include all classrooms in our analysis and randomly selected a classroom for each school to include. Additionally, because of variability in the classrooms, results varied depending on the classroom chosen. Due to these limitations, our results should be interpreted cautiously and are included in this tool described as either supporting or not supporting existing literature.